High Efficiency Solar Membranes Structurally Designed with 3D Core–2D Shell SiO<sub>2</sub>@Amino-Carbon Hybrid Advanced Composite for Facile Steam Generation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Steam generation through efficient utilization of solar energy is a promising technology in addressing the challenge of global freshwater shortage and water pollution. One of the biggest hurdles for traditional photothermal membranes to function continuously in a high temperature, high salt, and corrosive environment has been attributed to their rapid decline of mechanical properties. In this work, a highly efficient solar-driven interfacial water evaporation system has been developed via a polydopamine/carbon/silicon (PCS) composite membrane supported by a floating insulation foam substrate. A 3.1 fold increase in the water vaporization rate was recorded compared with the pure water system. The 2D-carbon nanolayer on the surface was successfully prepared by carbonizing low-cost linear polyethylene with a glass fiber (GF) membrane as the substrate, and then the carbon membrane was modified with dopamine to control water transport on the carbon coating and within the glass fiber. The PCS membrane has a high efficiency for solar steam generation owing to high optical absorption and has excellent solar thermal conversion capability. The evaporation rate and solar thermal conversion efficiency of the PCS membrane under simulated sunlight irradiation with 1 sun (1 kW·m–2) are 1.39 kg·m–2·h–1 and 80.4% respectively, which are significantly higher compared to GF membrane, carbon/silicon (CS) membrane, and pure water without a photothermal membrane. The water evaporation system retained high efficiency after 20 cycles under simulated sunlight irradiation of 1 sun. This study provides critical insight on the design and fabrication of a highly efficient and durable evaporation system.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it